• Nutrition · May 2024

    Comparison of bioelectrical impedance analysis and computed tomography for the assessment of muscle mass in patients with gastric cancer.

    • Junbo Zuo, Da Zhou, Li Zhang, Xiaodong Zhou, Xuejin Gao, Wenji Hou, Chen Wang, Pengcheng Jiang, and Xinying Wang.
    • Department of General Surgery, The Affiliated Jinling Hospital of Nanjing Medical University, Nanjing, China; Department of General Surgery, The Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
    • Nutrition. 2024 May 1; 121: 112363112363.

    BackgroundLow muscle mass was significantly correlated with poor clinical outcomes in cancer patients. This study aimed to compare the differences between bioelectrical impedance analysis (BIA) and computed tomography (CT) in measuring skeletal muscle mass and detecting low muscle mass in patients with gastric cancer (GC).MethodThis cross-sectional study included a total of 302 consecutive patients diagnosed with GC at our institution from October 2021 to March 2023. CT images were analyzed at the L3 level to obtain the cross-sectional area of skeletal muscle, which was subsequently used for calculating whole-body skeletal muscle mass via the Shen equation and skeletal muscle tissue density. BIA was utilized to measure skeletal muscle mass using the manufacturer's proprietary algorithms. Skeletal muscle mass (kg) was divided by height squared (m2) to obtain skeletal muscle index (SMI, kg/m2). Pearson's correlation coefficient was performed to assess the correlation between SMI measured by BIA and CT. The agreement between the two methods was assessed using Bland-Altman analyses. The clinically acceptable agreement was defined as the 95% limits of agreement (LOA) for the percentage bias falling within ± 10%. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of BIA in identifying low muscle mass.ResultsA total of 59 patients (19.5%) were identified as having low muscle mass based on CT analysis, whereas only 19 patients (6.3%) met the criteria for low muscle mass according to BIA analysis. BIA-measured SMI showed a strong positive correlation with CT-measured SMI in all patients (r = 0.715, P < 0.001). With Bland-Altman analysis, there was a significant mean bias of 1.18 ± 0.96 kg/m2 (95% CI 1.07-1.29, P < 0.001) between SMI measured by BIA and CT. The 95% LOA for the percentage bias ranged from -7.98 to 33.92%, which exceeded the clinically acceptable range of ± 10%. A significant difference was observed in the mean bias of SMI measured by BIA and CT between patients with and without GLIM malnutrition (1.42 ± 0.91 kg/m2 versus 0.98 ± 0.96 kg/m2, P < 0.001). The cut-off values for BIA-measured SMI in identifying low muscle mass using CT as the reference were 10.11 kg/m2 for males and 8.71 kg/m2 for females (male: AUC = 0.840, 95% CI: 0.772-0.908; female: AUC = 0.721, 95% CI: 0.598-0.843).ConclusionsDespite a significant correlation, the values of skeletal muscle mass obtained BIA and CT cannot be used interchangeably. The BIA method may overestimate skeletal muscle mass in GC patients compared to CT, especially among those with GLIM malnutrition, leading to an underestimation of low muscle mass prevalence.Copyright © 2024 Elsevier Inc. All rights reserved.

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